Peak performance
Keir Harman, head of asset management and optimisation services (AMOS) at Garrad Hassan, discusses optimising the operating
performance of wind farms
Performance monitoring and optimisation of conventional power generating plants that, typically, consist of only one or two turbines rated at several hundred MW, has been common practice for many decades. In contrast, a wind farm may contain tens, or even hundreds, of turbines rated at 1MW to 3MW each. The main focus of the wind industry to date has been on turbine availability - that is making sure that turbines are ready to generate or are generating. While this obviously remains a priority and a typical onshore wind farm owner can expect to achieve an average availability of 97 per cent (or three pre cent unscheduled downtime), there is unquestionable value in maintaining the efficiency of the turbines during their generating time but, in this respect, there is often surprisingly little work undertaken. To some extent, this is due to the sheer amount of data recorded which can make the prospect of analysis quite daunting. Statistics are, usually, recorded from hundreds of sensors around each individual turbine on a ten minute basis. While this volume of data can be incredibly valuable in helping to optimise the performance of a turbine, or an entire wind farm, it requires the use of sophisticated analytical tools combined with the knowledge of an experienced engineer, who will be able to perform the performance monitoring and diagnostic tasks.
As the wind farm industry reaches maturity, the size of wind farm investments has increased dramatically whilst profit margins have narrowed. As a result, there is a significant increase in the focus on optimising the performance of turbines and ensuring that they operate as designed.
Forecast
The key driver in the financial success of a wind farm project is the long-term energy yield forecast which is inextricably linked to revenue and, while an efficiency drop of one per cent will lead to a loss of project revenue of the same order, it could result in over ten per cent loss of profit for the owner. The yield forecast generally assumes that a turbine is running in perfect mechanical order and is highly efficient for the majority of the life of a project. This assumption is perfectly reasonable where the practice of frequent monitoring and optimisation is adopted.
The role of optimising performance is often the responsibility of the on-site wind farm technicians and managers yet they rarely have the tools, resources or facilities to do this. While they will be competent in fixing and maintaining turbines, their focus is usually on ensuring that they remain operational in often harsh weather conditions, rather than assessing the operating efficiency of the turbines. In fact, a drop in turbine efficiency is rarely apparent by inspecting the turbine itself: the only real means of identifying a problem is to analyse trends in the data recorded by each turbine.
Generally, the wind turbine warranty agreement will stipulate a guaranteed availability level, typically 97 per cent, for the first two or five years of the project. If the wind farm fails to achieve this level, the contractor will be liable to pay liquidated damages. This aspect of the contract is often clearly defined and is fairly straightforward to enforce. Similarly, there may be a clause to test the turbine power curve under the guidelines of international standards; however, this aspect is only designed to test the capability of the turbine model to reach the sales power curve over the period of the test and payment of damages for under-performance is very rare. The aspects of the typical contract associated with ongoing turbine operating efficiency are often vague, with little opportunity for a wind farm owner to claim back revenue lost due to periodic under-performance. It is therefore imperative that the owner works hard to keep the operating efficiency of the turbine high to maintain expected revenues.
The good news is that there are increasingly sophisticated tools available to assist in optimising performance. A standard wind farm SCADA system will already be recording most of the data required to monitor the operating efficiency of the turbines. A good place to start is to download all the ten minute average data for each turbine and assess the turbine power curves. The most useful parameters to use are wind speed, wind direction, turbine power, rotor speed and blade pitch angle. The power curves can be analysed by comparing relative power curves from turbine to turbine and, over time, using such a method means that drops in efficiency can be identified and followed by more ‘forensic’ type analysis of the data to diagnose the issue. Similar techniques can also be adopted to track temperature trends and component loading, to assess the likelihood of failures and ensure an optimised turbine lifetime. Issues that frequently affect turbine efficiency are: damaged components, incorrect control programme settings, poorly calibrated sensors and blade misalignment - problems that are often rectified at little cost.
Garrad Hassan, is an independent renewable energy consultancy serving the wind, marine and solar sectors worldwide. Our staff have assessed over 15GW of operating wind farms worldwide and, as a result, have gained a wealth of experience related to power performance optimisation. Some of the issues that we have identified have had a huge impact on the performance of turbines that, in some cases, have been experiencing drops in efficiency in the order of 30 per cent and, while many others have shown efficiency losses of just one or two per cent, these can have considerable impact on revenue, and therefore profit, if they remain undetected.
Future
Most wind farm performance monitoring and efficiency optimisation is currently done using sophisticated tools and, often, off-line as part of periodic desktop studies. In the future, it is likely that these techniques will, to some extent, be automated in the form of low frequency condition monitoring systems that are, ultimately, tasked with identifying problems when they occur in order to promote immediate remediation. The industry will retain its focus on optimising availability but will increasingly gear up to ensuring that turbines maintain an optimum efficiency at all times whilst generating.
As turbines become more dynamic they will also become more complex. This will result in increased propensity for under-performance, something which will eventually dictate the close performance monitoring of every turbine.
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